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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: S. Noël; M. Reuter; M. Buchwitz; J. Borchardt; +38 Authors

    We show new results from an updated version of the Fast atmOspheric traCe gAs retrievaL (FOCAL) retrieval method applied to measurements of the Greenhouse gases Observing SATellite (GOSAT) and its successor GOSAT-2. FOCAL was originally developed for estimating the total column carbon dioxide mixing ratio (XCO2) from spectral measurements made by the Orbiting Carbon Observatory-2 (OCO-2). However, depending on the available spectral windows, FOCAL also successfully retrieves total column amounts for other atmospheric species and their uncertainties within one single retrieval. The main focus of the current paper is on methane (XCH4; full-physics and proxy product), water vapour (XH2O) and the relative ratio of semi-heavy water (HDO) to water vapour (δD). Due to the extended spectral range of GOSAT-2, it is also possible to derive information on carbon monoxide (XCO) and nitrous oxide (XN2O) for which we also show first results. We also present an update on XCO2 from both instruments. For XCO2, the new FOCAL retrieval (v3.0) significantly increases the number of valid data compared with the previous FOCAL retrieval version (v1) by 50 % for GOSAT and about a factor of 2 for GOSAT-2 due to relaxed pre-screening and improved post-processing. All v3.0 FOCAL data products show reasonable spatial distribution and temporal variations. Comparisons with the Total Carbon Column Observing Network (TCCON) result in station-to-station biases which are generally in line with the reported TCCON uncertainties. With this updated version of the GOSAT-2 FOCAL data, we provide a first total column average XN2O product. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb, which can be explained by variations in tropopause height. The new GOSAT-2 XN2O product compares well with TCCON. Its station-to-station variability is lower than 2 ppb, which is about the magnitude of the typical N2O variations close to the surface. However, both GOSAT-2 and TCCON measurements show that the seasonal variations in the total column average XN2O are on the order of 8 ppb peak-to-peak, which can be easily resolved by the GOSAT-2 FOCAL data. Noting that only few XN2O measurements from satellites exist so far, the GOSAT-2 FOCAL product will be a valuable contribution in this context. International audience

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    https://doi.org/10.5445/ir/100...
    Article . 2022
    License: CC BY
    Data sources: Datacite
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    KITopen
    Article . 2022
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    Atmospheric Measurement Techniques
    Article . 2022 . Peer-reviewed
    License: CC BY
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      https://doi.org/10.5445/ir/100...
      Article . 2022
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      KITopen
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: B. Debus; A. T. Weakley; S. Takahama; K. M. George; +9 Authors

    To enable chemical speciation, monitoring networks collect particulate matter (PM) on different filter media, each subjected to one or more analytical techniques to quantify PM composition present in the atmosphere. In this work, we propose an alternate approach that uses one filter type (teflon or polytetrafluoroethylene, PTFE, commonly used for aerosol sampling) and one analytical method, Fourier transform infrared (FT-IR) spectroscopy to measure almost all of the major constituents in the aerosol. In the proposed method, measurements using the typical multi-filter, multi-analytical techniques are retained at a limited number of sites and used as calibration standards. At all remaining sites, only sampling on PTFE and analysis by FT-IR is performed. This method takes advantage of the sensitivity of the mid-IR domain to various organic and inorganic functional groups and offers a fast and inexpensive way of exploring sample composition. As a proof of concept, multiple years of samples collected within the Interagency Monitoring of PROtected Visual Environment network (IMPROVE) are explored with the aim of retaining high quality predictions for a broad range of atmospheric compounds including mass, organic (OC), elemental (EC), and total (TC) carbon, sulfate, nitrate, and crustal elements. Findings suggest that models based on only 21 sites, covering spatial and seasonal trends in atmospheric composition, are stable over a 3 year period within the IMPROVE network with acceptable prediction accuracy (R2 > 0.9, median bias less than 3 %) for most constituents. The major limitation is measuring nitrate as it is known to volatilize off of PTFE filters. Incorporating additional sites at low cost, partially replacing existing, more time- and cost-intensive techniques, or using the FT-IR data for quality control or substitute for missing data, are among the potential benefits of the one-filter, one-method approach.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ https://doi.org/10.5...arrow_drop_down
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    https://doi.org/10.5194/amt-20...
    Preprint . 2021 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    https://amt.copernicus.org/pre...
    Preprint
    License: CC BY
    Data sources: UnpayWall
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Atmospheric Measurement Techniques
    Article . 2022 . Peer-reviewed
    License: CC BY
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ https://doi.org/10.5...arrow_drop_down
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      https://doi.org/10.5194/amt-20...
      Preprint . 2021 . Peer-reviewed
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      Data sources: Crossref
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      https://amt.copernicus.org/pre...
      Preprint
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
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    Authors: Sang-Wook Lee; Sunghun Kim; Young-Suk Lee; Jae-Keun Yoo; +5 Authors

    A dual thermistor radiosonde (DTR) comprising two (aluminium-coated and black) sensors with different emissivities was developed to correct the effects of solar radiation on temperature probes based on in situ radiation measurements. Herein, the DTR performance is characterised in terms of the uncertainty via a series of ground-based facilities and an intercomparison radiosounding test. The DTR characterisation procedure using laboratory facilities is as follows: individually calibrate the temperature of the thermistors in a climate chamber from −70 to 30 ∘C to evaluate the uncertainty of raw temperature measurement before radiation correction; test the effect of temperature on the resistance reading using radiosonde boards in the climate chamber from −70 to 20 ∘C to identify a potential source of errors owing to the boards, especially at cold temperatures; individually perform radiation tests on thermistors at room temperature to investigate the degree of heating of aluminium-coated and black sensors (the average ratio = 1 : 2.4) and use the result for obtaining unit-specific radiation correction formulas; and perform parameterisation of the radiation measurement and correction formulas with five representative pairs of sensors in terms of temperature, pressure, ventilation speed, and irradiance using an upper air simulator. These results are combined and applied to the DTR sounding test conducted in July 2021. Thereafter, the effective irradiance is measured using the temperature difference between the aluminium-coated and black sensors of the DTR. The measured irradiance is then used for the radiation correction of the DTR aluminium-coated sensor. The radiation-corrected temperature of the DTR is mostly consistent with that of a commercial radiosonde (Vaisala, RS41) within the expanded uncertainty (∼ 0.35 ∘C) of the DTR at the coverage factor k = 2. Furthermore, the components contributing to the uncertainty of the radiation measurement and correction are analysed. The DTR methodology can improve the accuracy of temperature measurement in the upper air within the framework of the traceability to the International System of Units.

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    https://amt.copernicus.org/pre...
    Preprint
    License: CC BY
    Data sources: UnpayWall
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Atmospheric Measurement Techniques
    Article . 2022 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    https://doi.org/10.5194/amt-20...
    Preprint . 2021 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
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      https://doi.org/10.5194/amt-20...
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    Authors: Ashley S. Bittner; Eben S. Cross; David H. Hagan; Carl Malings; +2 Authors

    Low-cost gas and particulate matter sensor packages offer a compact, lightweight, and easily transportable solution to address global gaps in air quality (AQ) observations. However, regions that would benefit most from widespread deployment of low-cost AQ monitors often lack the reference-grade equipment required to reliably calibrate and validate them. In this study, we explore approaches to calibrating and validating three integrated sensor packages before a 1-year deployment to rural Malawi using colocation data collected at a regulatory site in North Carolina, USA. We compare the performance of five computational modeling approaches to calibrate the electrochemical gas sensors: k-nearest neighbors (kNN) hybrid, random forest (RF) hybrid, high-dimensional model representation (HDMR), multilinear regression (MLR), and quadratic regression (QR). For the CO, Ox, NO, and NO2 sensors, we found that kNN hybrid models returned the highest coefficients of determination and lowest error metrics when validated. Hybrid models were also the most transferable approach when applied to deployment data collected in Malawi. We compared kNN hybrid calibrated CO observations from two regions in Malawi to remote sensing data and found qualitative agreement in spatial and annual trends. However, ARISense monthly mean surface observations were 2 to 4 times higher than the remote sensing data, partly due to proximity to residential biomass combustion activity not resolved by satellite imaging. We also compared the performance of the integrated Alphasense OPC-N2 optical particle counter to a filter-corrected nephelometer using colocation data collected at one of our deployment sites in Malawi. We found the performance of the OPC-N2 varied widely with environmental conditions, with the worst performance associated with high relative humidity (RH >70 %) conditions and influence from emissions from nearby residential biomass combustion. We did not find obvious evidence of systematic sensor performance decay after the 1-year deployment to Malawi. Data recovery (30 %–80 %) varied by sensor and season and was limited by insufficient power and access to resources at the remote deployment sites. Future low-cost sensor deployments to rural, low-income settings would benefit from adaptable power systems, standardized sensor calibration methodologies, and increased regional regulatory-grade monitoring infrastructure.

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    https://doi.org/10.5194/amt-20...
    Preprint . 2021 . Peer-reviewed
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    Atmospheric Measurement Techniques
    Article . 2022 . Peer-reviewed
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      https://doi.org/10.5194/amt-20...
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
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    Authors: Jean-Claude Roger; Eric Vermote; Sergii Skakun; Emilie Murphy; +5 Authors

    Aerosols play a critical role in radiative transfer within the atmosphere, and they have a significant impact on climate change. As part of the validation of atmospheric correction of remote sensing data affected by the atmosphere, it is critical to utilize appropriate aerosol models as aerosols are a main source of error. In this paper, we propose and demonstrate a framework for building and identifying an aerosol model. For this purpose, we define the aerosol model by recalculating the aerosol microphysical properties (Cvf, Cvc, %Cvf, %Cvc, rvf, rvc, σr, σc, nr440, nr650, nr850, nr1020, ni440, ni650, ni850, ni1020, %Sph) based on the optical thickness at 440 nm τ440 and the Ångström coefficient α440–870 obtained from numerous AERosol RObotic NETwork (AERONET) sites. Using aerosol microphysical properties provided by the AERONET dataset, we were able to evaluate our own retrieved microphysical properties. The associated uncertainties are up to 23 %, except for the challenging, imaginary part of the refractive index ni (about 38 %). Uncertainties of the retrieved aerosol microphysical properties were incorporated in the framework for validating surface reflectance derived from space-borne Earth observation sensors. Results indicate that the impact of aerosol microphysical properties varies 3.5 × 10−5 to 10−3 in reflectance units. Finally, the uncertainties of the microphysical properties yielded an overall uncertainty of approximately of 1 to 3 % of the retrieved surface reflectance in the MODIS red spectral band (620–670 nm), which corresponds to the specification used for atmospheric correction.

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    https://doi.org/10.5194/amt-20...
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    https://doi.org/10.1109/igarss...
    Conference object . 2022 . Peer-reviewed
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      https://doi.org/10.5194/amt-20...
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      https://doi.org/10.1109/igarss...
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    Authors: Pu Jiang; Jinlong Yuan; Kenan Wu; Lu Wang; +1 Authors

    The refractive index structure constant (Cn2) is a key parameter used in describing the influence of turbulence on laser transmissions in the atmosphere. Three different methods for estimating Cn2 were analyzed in detail. A new method that uses a combination of these methods for continuous Cn2 profiling with both high temporal and spatial resolution is proposed and demonstrated. Under the assumption of the Kolmogorov “2/3 law”, the Cn2 profile can be calculated by using the wind field and turbulent kinetic energy dissipation rate (TKEDR) measured by coherent Doppler wind lidar (CDWL) and other meteorological parameters derived from a microwave radiometer (MWR). In a horizontal experiment, a comparison between the results from our new method and measurements made by a large aperture scintillometer (LAS) is conducted. The correlation coefficient, mean error, and standard deviation between them in a six-day observation are 0.8073, 8.18 × 10−16 m−2/3 and 1.27 × 10−15 m−2/3, respectively. In the vertical direction, the continuous profiling results of Cn2 and other turbulence parameters with high resolution in the atmospheric boundary layer (ABL) are retrieved. In addition, the limitation and uncertainty of this method under different circumstances were analyzed, which shows that the relative error of Cn2 estimation normally does not exceed 30% under the convective boundary layer (CBL).

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    https://doi.org/10.5194/amt-20...
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      https://doi.org/10.5194/amt-20...
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    Authors: Vivienne H. Payne; Susan S. Kulawik; Emily V. Fischer; Jared F. Brewer; +8 Authors

    We present an overview of an optimal estimation algorithm to retrieve peroxyacetyl nitrate (PAN) from single-field-of-view Level 1B radiances measured by the Cross-Track Infrared Sounder (CrIS). CrIS PAN retrievals show peak sensitivity in the mid-troposphere, with degrees of freedom for signal less than or equal to 1.0. We show comparisons with two sets of aircraft measurements from the Atmospheric Tomography Mission (ATom), the PAN and Trace Hydrohalocarbon ExpeRiment (PANTHER) and the Georgia Tech chemical ionization mass spectrometer (GT-CIMS). We find a systematic difference between the two aircraft datasets, with vertically averaged mid-tropospheric values from the GT-CIMS around 14 % lower than equivalent values from PANTHER. However, the two sets of aircraft measurements are strongly correlated (R2 value of 0.92) and do provide a consistent view of the large-scale variation of PAN. We demonstrate that the retrievals of PAN from CrIS show skill in measurement of these large-scale PAN distributions in the remote mid-troposphere compared to the retrieval prior. The standard deviation of individual CrIS–aircraft differences is 0.08 ppbv, which we take as an estimate of the uncertainty of the CrIS mid-tropospheric PAN for a single satellite field of view. The standard deviation of the CrIS–aircraft comparisons for averaged CrIS retrievals (median of 20 satellite coincidences with each aircraft profile) is lower at 0.05 ppbv. This would suggest that the retrieval error is reduced with averaging, although not with the square root of the number of observations. We find a negative bias of the order of 0.1 ppbv in the CrIS PAN results with respect to the aircraft measurements. This bias shows a dependence on column water vapor. We provide a water-vapor-dependent bias correction for use with the CrIS PAN data.

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    Atmospheric Measurement Techniques
    Article . 2022 . Peer-reviewed
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    https://doi.org/10.5194/amt-20...
    Preprint . 2021 . Peer-reviewed
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
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      https://doi.org/10.5194/amt-20...
      Preprint . 2021 . Peer-reviewed
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    Authors: Gregor Köcher; Tobias Zinner; Christoph Knote; Eleni Tetoni; +2 Authors

    Abstract. The representation of cloud microphysical processes contributes substantially to the uncertainty of numerical weather simulations. In part, this is owed to some fundamental knowledge gaps in the underlying processes due to the difficulty of observing them directly. On the path to closing these gaps, we present a setup for the systematic characterization of differences between numerical weather model and radar observations for convective weather situations. Radar observations are introduced which provide targeted dual-wavelength and polarimetric measurements of convective clouds with the potential to provide more detailed information about hydrometeor shapes and sizes. A convection-permitting regional weather model setup is established using five different microphysics schemes (double-moment, spectral bin (“Fast Spectral Bin Microphysics”, FSBM), and particle property prediction (P3)). Observations are compared to hindcasts which are created with a polarimetric radar forward simulator for all measurement days. A cell-tracking algorithm applied to radar and model data facilitates comparison on a cell object basis. Statistical comparisons of radar observations and numerical weather model runs are presented on a data set of 30 convection days. In general, simulations show too few weak and small-scale convective cells. Contoured frequency by altitude diagrams of radar signatures reveal deviations between the schemes and observations in ice and liquid phase. Apart from the P3 scheme, high reflectivities in the ice phase are simulated too frequently. Dual-wavelength signatures demonstrate issues of most schemes to correctly represent ice particle size distributions, producing too large or too dense graupel particles. Comparison of polarimetric radar signatures reveals issues of all schemes except the FSBM to correctly represent rain particle size distributions.

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    Atmospheric Measurement Techniques
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    OPUS Augsburg
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    Atmospheric Measurement Techniques
    Article . 2022 . Peer-reviewed
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    https://doi.org/10.5194/amt-20...
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    OPUS Augsburg
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      Atmospheric Measurement Techniques
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      Atmospheric Measurement Techniques
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      https://doi.org/10.5194/amt-20...
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      OPUS Augsburg
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    Authors: L. Lei; L. Lei; T. A. Berkoff; G. Gronoff; +8 Authors

    Aerosols emitted from wildfires are becoming one of the main sources of poor air quality in the US mainland. Their extinction in UVB (wavelength range 280–315 nm) is difficult to be retrieved using simple lidar techniques because of the impact of O3 absorption and lacking information of lidar ratio at those wavelengths. The 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) campaign in the New York City region allowed the characterization of lidar ratio for UVB aerosol retrieval. An algorithm for the aerosol extinction retrieval out of the Langley Mobile Ozone Lidar (LMOL) was used in conjunction with the NASA Langley High Altitude Lidar Observatory (HALO) 532 nm aerosol extinction product. This approach requires assuming 2 parameters, the lidar ratio at 292 nm and the Ångström Exponent (AE) between 532 nm and 292 nm. The objective of this work is to determine these two parameters and assess the retrieval error caused by improper assumption of lidar ratio. This work also accomplishes the first know 292 nm aerosol product inter-comparison between HALO and Tropospheric Ozone Lidar Network (TOLNet) ozone lidar. HALO results were compared with the aerosol data retrieved from the 292 nm band from LMOL with different approximations of the lidar ratio and the AE to determine optimal parameters. Using optimized parameters, the LMOL aerosol extinction can be retrieved with a 10 % accuracy up to 3 km. This work highlights the importance of the lidar ratio and AE in the retrieval and validation of 292 nm aerosol profiles obtained from UV-lidar. Errors arise from approaches that utilize a random priori lidar ratio and AE assumption. The lidar ratios at 292 nm determined in this work will also improve our understanding of the UVB optical properties of aerosol in the lower troposphere affected by transported wildfire emission.

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    https://doi.org/10.5194/amt-20...
    Preprint . 2021 . Peer-reviewed
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    Atmospheric Measurement Techniques
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      https://doi.org/10.5194/amt-20...
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      Atmospheric Measurement Techniques
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Shih-Chiao Tsai; Yen Hsyang Chu; Jenn-Shyong Chen;

    Abstract. The Chung-Li very-high-frequency (VHF at 52 MHz) atmospheric radar and a dual-polarized microwave radiometer were operated collaboratively to investigate strongly convective precipitation while the typhoon Trami just passed through the Taiwan in Aug, 2013. First, respective Doppler velocities of clear-air and precipitation echoes were identified automatically by the VHF radar as clearly as possible. Two approaches were designed for this purpose: contour-based and peak-finding processes. The two approaches initially determined some major spectral centers or peaks, which were usually redundant, and then proper sifting and clustering were performed for the redundant spectral centers or peaks to yield several mean locations of Doppler velocities for profiling. The outcomes of the two approaches were consistent in general. With the estimated Doppler velocities, a tracing process was developed for Doppler profiling, in which Doppler velocity shear was one of the significant criteria in the tracing process. The radar echoes collected by the VHF radar during rainy and strongly convective atmosphere have been investigated to validate the two approaches and the tracing process. About 98 % of the tracings could identify the Doppler profiles of clear air and precipitation, even the atmosphere was disturbed severely. The radar spectral parameters, Doppler profiles, and the information from a dual-polarized microwave radiometer as well as the simulation of weather model, were examined jointly. It signified that strong updraft and turbulent atmosphere could bring the liquid water to the height above the melting layer, and then the Bergeron effect and coalescence process on formation of ice crystal and graupel above the height of the melting layer occurred accordingly.

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    https://amt.copernicus.org/pre...
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    https://doi.org/10.5194/amt-20...
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: S. Noël; M. Reuter; M. Buchwitz; J. Borchardt; +38 Authors

    We show new results from an updated version of the Fast atmOspheric traCe gAs retrievaL (FOCAL) retrieval method applied to measurements of the Greenhouse gases Observing SATellite (GOSAT) and its successor GOSAT-2. FOCAL was originally developed for estimating the total column carbon dioxide mixing ratio (XCO2) from spectral measurements made by the Orbiting Carbon Observatory-2 (OCO-2). However, depending on the available spectral windows, FOCAL also successfully retrieves total column amounts for other atmospheric species and their uncertainties within one single retrieval. The main focus of the current paper is on methane (XCH4; full-physics and proxy product), water vapour (XH2O) and the relative ratio of semi-heavy water (HDO) to water vapour (δD). Due to the extended spectral range of GOSAT-2, it is also possible to derive information on carbon monoxide (XCO) and nitrous oxide (XN2O) for which we also show first results. We also present an update on XCO2 from both instruments. For XCO2, the new FOCAL retrieval (v3.0) significantly increases the number of valid data compared with the previous FOCAL retrieval version (v1) by 50 % for GOSAT and about a factor of 2 for GOSAT-2 due to relaxed pre-screening and improved post-processing. All v3.0 FOCAL data products show reasonable spatial distribution and temporal variations. Comparisons with the Total Carbon Column Observing Network (TCCON) result in station-to-station biases which are generally in line with the reported TCCON uncertainties. With this updated version of the GOSAT-2 FOCAL data, we provide a first total column average XN2O product. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb, which can be explained by variations in tropopause height. The new GOSAT-2 XN2O product compares well with TCCON. Its station-to-station variability is lower than 2 ppb, which is about the magnitude of the typical N2O variations close to the surface. However, both GOSAT-2 and TCCON measurements show that the seasonal variations in the total column average XN2O are on the order of 8 ppb peak-to-peak, which can be easily resolved by the GOSAT-2 FOCAL data. Noting that only few XN2O measurements from satellites exist so far, the GOSAT-2 FOCAL product will be a valuable contribution in this context. International audience

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    https://doi.org/10.5445/ir/100...
    Article . 2022
    License: CC BY
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    KITopen
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    Atmospheric Measurement Techniques
    Article . 2022 . Peer-reviewed
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      https://doi.org/10.5445/ir/100...
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      KITopen
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: B. Debus; A. T. Weakley; S. Takahama; K. M. George; +9 Authors

    To enable chemical speciation, monitoring networks collect particulate matter (PM) on different filter media, each subjected to one or more analytical techniques to quantify PM composition present in the atmosphere. In this work, we propose an alternate approach that uses one filter type (teflon or polytetrafluoroethylene, PTFE, commonly used for aerosol sampling) and one analytical method, Fourier transform infrared (FT-IR) spectroscopy to measure almost all of the major constituents in the aerosol. In the proposed method, measurements using the typical multi-filter, multi-analytical techniques are retained at a limited number of sites and used as calibration standards. At all remaining sites, only sampling on PTFE and analysis by FT-IR is performed. This method takes advantage of the sensitivity of the mid-IR domain to various organic and inorganic functional groups and offers a fast and inexpensive way of exploring sample composition. As a proof of concept, multiple years of samples collected within the Interagency Monitoring of PROtected Visual Environment network (IMPROVE) are explored with the aim of retaining high quality predictions for a broad range of atmospheric compounds including mass, organic (OC), elemental (EC), and total (TC) carbon, sulfate, nitrate, and crustal elements. Findings suggest that models based on only 21 sites, covering spatial and seasonal trends in atmospheric composition, are stable over a 3 year period within the IMPROVE network with acceptable prediction accuracy (R2 > 0.9, median bias less than 3 %) for most constituents. The major limitation is measuring nitrate as it is known to volatilize off of PTFE filters. Incorporating additional sites at low cost, partially replacing existing, more time- and cost-intensive techniques, or using the FT-IR data for quality control or substitute for missing data, are among the potential benefits of the one-filter, one-method approach.

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    https://doi.org/10.5194/amt-20...
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    Atmospheric Measurement Techniques
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      https://doi.org/10.5194/amt-20...
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      Atmospheric Measurement Techniques
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    Authors: Sang-Wook Lee; Sunghun Kim; Young-Suk Lee; Jae-Keun Yoo; +5 Authors

    A dual thermistor radiosonde (DTR) comprising two (aluminium-coated and black) sensors with different emissivities was developed to correct the effects of solar radiation on temperature probes based on in situ radiation measurements. Herein, the DTR performance is characterised in terms of the uncertainty via a series of ground-based facilities and an intercomparison radiosounding test. The DTR characterisation procedure using laboratory facilities is as follows: individually calibrate the temperature of the thermistors in a climate chamber from −70 to 30 ∘C to evaluate the uncertainty of raw temperature measurement before radiation correction; test the effect of temperature on the resistance reading using radiosonde boards in the climate chamber from −70 to 20 ∘C to identify a potential source of errors owing to the boards, especially at cold temperatures; individually perform radiation tests on thermistors at room temperature to investigate the degree of heating of aluminium-coated and black sensors (the average ratio = 1 : 2.4) and use the result for obtaining unit-specific radiation correction formulas; and perform parameterisation of the radiation measurement and correction formulas with five representative pairs of sensors in terms of temperature, pressure, ventilation speed, and irradiance using an upper air simulator. These results are combined and applied to the DTR sounding test conducted in July 2021. Thereafter, the effective irradiance is measured using the temperature difference between the aluminium-coated and black sensors of the DTR. The measured irradiance is then used for the radiation correction of the DTR aluminium-coated sensor. The radiation-corrected temperature of the DTR is mostly consistent with that of a commercial radiosonde (Vaisala, RS41) within the expanded uncertainty (∼ 0.35 ∘C) of the DTR at the coverage factor k = 2. Furthermore, the components contributing to the uncertainty of the radiation measurement and correction are analysed. The DTR methodology can improve the accuracy of temperature measurement in the upper air within the framework of the traceability to the International System of Units.

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    Atmospheric Measurement Techniques
    Article . 2022 . Peer-reviewed
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    https://doi.org/10.5194/amt-20...
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
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      https://doi.org/10.5194/amt-20...
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    Authors: Ashley S. Bittner; Eben S. Cross; David H. Hagan; Carl Malings; +2 Authors

    Low-cost gas and particulate matter sensor packages offer a compact, lightweight, and easily transportable solution to address global gaps in air quality (AQ) observations. However, regions that would benefit most from widespread deployment of low-cost AQ monitors often lack the reference-grade equipment required to reliably calibrate and validate them. In this study, we explore approaches to calibrating and validating three integrated sensor packages before a 1-year deployment to rural Malawi using colocation data collected at a regulatory site in North Carolina, USA. We compare the performance of five computational modeling approaches to calibrate the electrochemical gas sensors: k-nearest neighbors (kNN) hybrid, random forest (RF) hybrid, high-dimensional model representation (HDMR), multilinear regression (MLR), and quadratic regression (QR). For the CO, Ox, NO, and NO2 sensors, we found that kNN hybrid models returned the highest coefficients of determination and lowest error metrics when validated. Hybrid models were also the most transferable approach when applied to deployment data collected in Malawi. We compared kNN hybrid calibrated CO observations from two regions in Malawi to remote sensing data and found qualitative agreement in spatial and annual trends. However, ARISense monthly mean surface observations were 2 to 4 times higher than the remote sensing data, partly due to proximity to residential biomass combustion activity not resolved by satellite imaging. We also compared the performance of the integrated Alphasense OPC-N2 optical particle counter to a filter-corrected nephelometer using colocation data collected at one of our deployment sites in Malawi. We found the performance of the OPC-N2 varied widely with environmental conditions, with the worst performance associated with high relative humidity (RH >70 %) conditions and influence from emissions from nearby residential biomass combustion. We did not find obvious evidence of systematic sensor performance decay after the 1-year deployment to Malawi. Data recovery (30 %–80 %) varied by sensor and season and was limited by insufficient power and access to resources at the remote deployment sites. Future low-cost sensor deployments to rural, low-income settings would benefit from adaptable power systems, standardized sensor calibration methodologies, and increased regional regulatory-grade monitoring infrastructure.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ https://doi.org/10.5...arrow_drop_down
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    https://doi.org/10.5194/amt-20...
    Preprint . 2021 . Peer-reviewed
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    Atmospheric Measurement Techniques
    Article . 2022 . Peer-reviewed
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      https://doi.org/10.5194/amt-20...
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
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    Authors: Jean-Claude Roger; Eric Vermote; Sergii Skakun; Emilie Murphy; +5 Authors

    Aerosols play a critical role in radiative transfer within the atmosphere, and they have a significant impact on climate change. As part of the validation of atmospheric correction of remote sensing data affected by the atmosphere, it is critical to utilize appropriate aerosol models as aerosols are a main source of error. In this paper, we propose and demonstrate a framework for building and identifying an aerosol model. For this purpose, we define the aerosol model by recalculating the aerosol microphysical properties (Cvf, Cvc, %Cvf, %Cvc, rvf, rvc, σr, σc, nr440, nr650, nr850, nr1020, ni440, ni650, ni850, ni1020, %Sph) based on the optical thickness at 440 nm τ440 and the Ångström coefficient α440–870 obtained from numerous AERosol RObotic NETwork (AERONET) sites. Using aerosol microphysical properties provided by the AERONET dataset, we were able to evaluate our own retrieved microphysical properties. The associated uncertainties are up to 23 %, except for the challenging, imaginary part of the refractive index ni (about 38 %). Uncertainties of the retrieved aerosol microphysical properties were incorporated in the framework for validating surface reflectance derived from space-borne Earth observation sensors. Results indicate that the impact of aerosol microphysical properties varies 3.5 × 10−5 to 10−3 in reflectance units. Finally, the uncertainties of the microphysical properties yielded an overall uncertainty of approximately of 1 to 3 % of the retrieved surface reflectance in the MODIS red spectral band (620–670 nm), which corresponds to the specification used for atmospheric correction.

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    https://doi.org/10.5194/amt-20...
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    https://doi.org/10.1109/igarss...
    Conference object . 2022 . Peer-reviewed
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      https://doi.org/10.5194/amt-20...
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      https://doi.org/10.1109/igarss...
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    Authors: Pu Jiang; Jinlong Yuan; Kenan Wu; Lu Wang; +1 Authors

    The refractive index structure constant (Cn2) is a key parameter used in describing the influence of turbulence on laser transmissions in the atmosphere. Three different methods for estimating Cn2 were analyzed in detail. A new method that uses a combination of these methods for continuous Cn2 profiling with both high temporal and spatial resolution is proposed and demonstrated. Under the assumption of the Kolmogorov “2/3 law”, the Cn2 profile can be calculated by using the wind field and turbulent kinetic energy dissipation rate (TKEDR) measured by coherent Doppler wind lidar (CDWL) and other meteorological parameters derived from a microwave radiometer (MWR). In a horizontal experiment, a comparison between the results from our new method and measurements made by a large aperture scintillometer (LAS) is conducted. The correlation coefficient, mean error, and standard deviation between them in a six-day observation are 0.8073, 8.18 × 10−16 m−2/3 and 1.27 × 10−15 m−2/3, respectively. In the vertical direction, the continuous profiling results of Cn2 and other turbulence parameters with high resolution in the atmospheric boundary layer (ABL) are retrieved. In addition, the limitation and uncertainty of this method under different circumstances were analyzed, which shows that the relative error of Cn2 estimation normally does not exceed 30% under the convective boundary layer (CBL).

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    Remote Sensing
    Other literature type . Article . 2022 . Peer-reviewed
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    Article . 2022
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    https://doi.org/10.5194/amt-20...
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      https://doi.org/10.5194/amt-20...
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Vivienne H. Payne; Susan S. Kulawik; Emily V. Fischer; Jared F. Brewer; +8 Authors

    We present an overview of an optimal estimation algorithm to retrieve peroxyacetyl nitrate (PAN) from single-field-of-view Level 1B radiances measured by the Cross-Track Infrared Sounder (CrIS). CrIS PAN retrievals show peak sensitivity in the mid-troposphere, with degrees of freedom for signal less than or equal to 1.0. We show comparisons with two sets of aircraft measurements from the Atmospheric Tomography Mission (ATom), the PAN and Trace Hydrohalocarbon ExpeRiment (PANTHER) and the Georgia Tech chemical ionization mass spectrometer (GT-CIMS). We find a systematic difference between the two aircraft datasets, with vertically averaged mid-tropospheric values from the GT-CIMS around 14 % lower than equivalent values from PANTHER. However, the two sets of aircraft measurements are strongly correlated (R2 value of 0.92) and do provide a consistent view of the large-scale variation of PAN. We demonstrate that the retrievals of PAN from CrIS show skill in measurement of these large-scale PAN distributions in the remote mid-troposphere compared to the retrieval prior. The standard deviation of individual CrIS–aircraft differences is 0.08 ppbv, which we take as an estimate of the uncertainty of the CrIS mid-tropospheric PAN for a single satellite field of view. The standard deviation of the CrIS–aircraft comparisons for averaged CrIS retrievals (median of 20 satellite coincidences with each aircraft profile) is lower at 0.05 ppbv. This would suggest that the retrieval error is reduced with averaging, although not with the square root of the number of observations. We find a negative bias of the order of 0.1 ppbv in the CrIS PAN results with respect to the aircraft measurements. This bias shows a dependence on column water vapor. We provide a water-vapor-dependent bias correction for use with the CrIS PAN data.

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    Atmospheric Measurement Techniques
    Article . 2022 . Peer-reviewed
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    https://doi.org/10.5194/amt-20...
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
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      https://doi.org/10.5194/amt-20...
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    Authors: Gregor Köcher; Tobias Zinner; Christoph Knote; Eleni Tetoni; +2 Authors

    Abstract. The representation of cloud microphysical processes contributes substantially to the uncertainty of numerical weather simulations. In part, this is owed to some fundamental knowledge gaps in the underlying processes due to the difficulty of observing them directly. On the path to closing these gaps, we present a setup for the systematic characterization of differences between numerical weather model and radar observations for convective weather situations. Radar observations are introduced which provide targeted dual-wavelength and polarimetric measurements of convective clouds with the potential to provide more detailed information about hydrometeor shapes and sizes. A convection-permitting regional weather model setup is established using five different microphysics schemes (double-moment, spectral bin (“Fast Spectral Bin Microphysics”, FSBM), and particle property prediction (P3)). Observations are compared to hindcasts which are created with a polarimetric radar forward simulator for all measurement days. A cell-tracking algorithm applied to radar and model data facilitates comparison on a cell object basis. Statistical comparisons of radar observations and numerical weather model runs are presented on a data set of 30 convection days. In general, simulations show too few weak and small-scale convective cells. Contoured frequency by altitude diagrams of radar signatures reveal deviations between the schemes and observations in ice and liquid phase. Apart from the P3 scheme, high reflectivities in the ice phase are simulated too frequently. Dual-wavelength signatures demonstrate issues of most schemes to correctly represent ice particle size distributions, producing too large or too dense graupel particles. Comparison of polarimetric radar signatures reveals issues of all schemes except the FSBM to correctly represent rain particle size distributions.

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    Atmospheric Measurement Techniques
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    OPUS Augsburg
    Article . 2022
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    Atmospheric Measurement Techniques
    Article . 2022 . Peer-reviewed
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    https://doi.org/10.5194/amt-20...
    Preprint . 2021 . Peer-reviewed
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    OPUS Augsburg
    Article . 2022
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      Atmospheric Measurement Techniques
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
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      https://doi.org/10.5194/amt-20...
      Preprint . 2021 . Peer-reviewed
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      OPUS Augsburg
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    Authors: L. Lei; L. Lei; T. A. Berkoff; G. Gronoff; +8 Authors

    Aerosols emitted from wildfires are becoming one of the main sources of poor air quality in the US mainland. Their extinction in UVB (wavelength range 280–315 nm) is difficult to be retrieved using simple lidar techniques because of the impact of O3 absorption and lacking information of lidar ratio at those wavelengths. The 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) campaign in the New York City region allowed the characterization of lidar ratio for UVB aerosol retrieval. An algorithm for the aerosol extinction retrieval out of the Langley Mobile Ozone Lidar (LMOL) was used in conjunction with the NASA Langley High Altitude Lidar Observatory (HALO) 532 nm aerosol extinction product. This approach requires assuming 2 parameters, the lidar ratio at 292 nm and the Ångström Exponent (AE) between 532 nm and 292 nm. The objective of this work is to determine these two parameters and assess the retrieval error caused by improper assumption of lidar ratio. This work also accomplishes the first know 292 nm aerosol product inter-comparison between HALO and Tropospheric Ozone Lidar Network (TOLNet) ozone lidar. HALO results were compared with the aerosol data retrieved from the 292 nm band from LMOL with different approximations of the lidar ratio and the AE to determine optimal parameters. Using optimized parameters, the LMOL aerosol extinction can be retrieved with a 10 % accuracy up to 3 km. This work highlights the importance of the lidar ratio and AE in the retrieval and validation of 292 nm aerosol profiles obtained from UV-lidar. Errors arise from approaches that utilize a random priori lidar ratio and AE assumption. The lidar ratios at 292 nm determined in this work will also improve our understanding of the UVB optical properties of aerosol in the lower troposphere affected by transported wildfire emission.

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    https://doi.org/10.5194/amt-20...
    Preprint . 2021 . Peer-reviewed
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    Atmospheric Measurement Techniques
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      https://doi.org/10.5194/amt-20...
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      Atmospheric Measurement Techniques
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    Authors: Shih-Chiao Tsai; Yen Hsyang Chu; Jenn-Shyong Chen;

    Abstract. The Chung-Li very-high-frequency (VHF at 52 MHz) atmospheric radar and a dual-polarized microwave radiometer were operated collaboratively to investigate strongly convective precipitation while the typhoon Trami just passed through the Taiwan in Aug, 2013. First, respective Doppler velocities of clear-air and precipitation echoes were identified automatically by the VHF radar as clearly as possible. Two approaches were designed for this purpose: contour-based and peak-finding processes. The two approaches initially determined some major spectral centers or peaks, which were usually redundant, and then proper sifting and clustering were performed for the redundant spectral centers or peaks to yield several mean locations of Doppler velocities for profiling. The outcomes of the two approaches were consistent in general. With the estimated Doppler velocities, a tracing process was developed for Doppler profiling, in which Doppler velocity shear was one of the significant criteria in the tracing process. The radar echoes collected by the VHF radar during rainy and strongly convective atmosphere have been investigated to validate the two approaches and the tracing process. About 98 % of the tracings could identify the Doppler profiles of clear air and precipitation, even the atmosphere was disturbed severely. The radar spectral parameters, Doppler profiles, and the information from a dual-polarized microwave radiometer as well as the simulation of weather model, were examined jointly. It signified that strong updraft and turbulent atmosphere could bring the liquid water to the height above the melting layer, and then the Bergeron effect and coalescence process on formation of ice crystal and graupel above the height of the melting layer occurred accordingly.

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    https://doi.org/10.5194/amt-20...
    Preprint . 2021 . Peer-reviewed
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